mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
James Sawyer
117 lines
3.0 KiB
Python
117 lines
3.0 KiB
Python
# -*- coding: utf-8 -*-
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from pandas_ta.overlap import linreg
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from pandas_ta.volatility import rvi
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from pandas_ta.utils import get_drift, get_offset, non_zero_range, verify_series
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def inertia(
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close=None,
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high=None,
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low=None,
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length=None,
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rvi_length=None,
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scalar=None,
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refined=None,
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thirds=None,
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mamode=None,
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drift=None,
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offset=None,
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**kwargs,
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):
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"""Indicator: Inertia (INERTIA)"""
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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 20
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rvi_length = int(rvi_length) if rvi_length and rvi_length > 0 else 14
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scalar = float(scalar) if scalar and scalar > 0 else 100
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refined = False if refined is None else True
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thirds = False if thirds is None else True
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drift = get_drift(drift)
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offset = get_offset(offset)
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if refined or thirds:
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high = verify_series(high)
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low = verify_series(low)
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# Calculate Result
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_mode = ""
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if refined:
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rvi_ = rvi(
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close,
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high=high,
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low=low,
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length=rvi_length,
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scalar=scalar,
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refined=refined,
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mamode=mamode,
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)
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_mode = "r"
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elif thirds:
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rvi_ = rvi(
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close,
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high=high,
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low=low,
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length=rvi_length,
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scalar=scalar,
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thirds=thirds,
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mamode=mamode,
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)
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_mode = "t"
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else:
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rvi_ = rvi(close, length=rvi_length, scalar=scalar, mamode=mamode)
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inertia = linreg(rvi_, length=length)
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# Offset
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if offset != 0:
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inertia = inertia.shift(offset)
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# Handle fills
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if "fillna" in kwargs:
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inertia.fillna(kwargs["fillna"], inplace=True)
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if "fill_method" in kwargs:
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inertia.fillna(method=kwargs["fill_method"], inplace=True)
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# Name & Category
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_props = f"_{length}_{rvi_length}"
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inertia.name = f"INERTIA{_mode}{_props}"
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inertia.category = "momentum"
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return inertia
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inertia.__doc__ = """Inertia (INERTIA)
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Inertia was developed by Donald Dorsey and was introduced his article
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in September, 1995. It is the Relative Vigor Index smoothed by the Least
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Squares Moving Average. Postive Inertia when values are greater than 50,
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Negative Inertia otherwise.
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Sources:
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https://www.investopedia.com/terms/r/relative_vigor_index.asp
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Calculation:
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Default Inputs:
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length=14, ma_length=20
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LSQRMA = Least Squares Moving Average
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INERTIA = LSQRMA(RVI(length), ma_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): It's period. Default: 20
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rvi_length (int): RVI period. Default: 14
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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.Series: New feature generated.
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"""
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