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72 lines
2.2 KiB
Python
72 lines
2.2 KiB
Python
# -*- coding: utf-8 -*-
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from pandas import Series
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from pandas_ta._typing import DictLike, Int, IntFloat
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from pandas_ta.utils import v_float, v_offset, v_series
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def remap(
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close: Series, from_min: IntFloat = None, from_max: IntFloat = None,
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to_min: IntFloat = None, to_max: IntFloat = None,
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offset: Int = None, **kwargs: DictLike
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) -> Series:
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"""
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Indicator: ReMap (REMAP)
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Basically a static normalizer, which maps the input min and max to a given
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output range. Many range bound oscillators move between 0 and 100, but
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there are also other variants. Refer to the example below or add more the
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list.
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Examples:
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RSI -> IFISHER: from_min=0, from_max=100, to_min=-1, to_max=1.0
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Sources:
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rengel8 for Pandas TA
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Args:
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close (pd.Series): Series of 'close's
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from_min (float): Input minimum. Default: 0.0
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from_max (float): Input maximum. Default: 100.0
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to_min (float): Output minimum. Default: 0.0
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to_max (float): Output maximum. Default: 100.0
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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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# Validate
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close = v_series(close)
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from_min = v_float(from_min, 0.0, 0.0)
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from_max = v_float(from_max, 100.0, 0.0)
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to_min = v_float(to_min, -1.0, 0.0)
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to_max = v_float(to_max, 1.0, 0.0)
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offset = v_offset(offset)
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# Calculate
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frange, trange = from_max - from_min, to_max - to_min
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if frange <= 0 or trange <= 0:
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return
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result = to_min + (trange / frange) * (close.values - from_min)
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result = Series(result, index=close.index)
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# Offset
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if offset != 0:
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result = result.shift(offset)
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# Fill
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if "fillna" in kwargs:
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result.fillna(kwargs["fillna"], inplace=True)
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if "fill_method" in kwargs:
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result.fillna(method=kwargs["fill_method"], inplace=True)
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# Name and Category
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result.name = f"REMAP_{from_min}_{from_max}_{to_min}_{to_max}"
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# result.name = f"{close.name}_{from_min}_{from_max}_{to_min}_{to_max}" # OR
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result.category = "transform"
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return result
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