Source code for feets.extractors.ext_inter_percentile_range
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2017-2024, Cabral, Juan
# Copyright (c) 2025, QuatroPe; Clariá, Felipe
# License: MIT
# Full Text:
# https://github.com/quatrope/feets/blob/master/LICENSE
# =============================================================================
# DOC
# =============================================================================
"""Inter-percentile range extractor."""
# =============================================================================
# IMPORTS
# =============================================================================
from light_curve import InterPercentileRange as _InterPercentileRange
from .light_curve_extractor import LightCurveExtractor
from ..libs import doctools
# =============================================================================
# EXTRACTOR CLASS
# =============================================================================
[docs]
class InterPercentileRange(LightCurveExtractor):
"""Inter-percentile range.
.. math::
Q(1 - p) - Q(p)
where :math:`Q(p)` is the :math:`p`-th quantile of the magnitude
distribution.
Special cases are the interquartile range which is inter-percentile range
for :math:`p = 0.25`, and the interdecile range, which is inter-percentile
range for :math:`p = 0.1`.
Parameters
----------
quantile : positive float, default=0.25
Range is
:math:`(100%% * quantile, 100%% * (1 - quantile))`.
Default quantile is 0.25
transform : str or bool or None, optional
Transformer to apply to the feature values. If str, must be one of:
- 'default' - use default transformer for the feature, it same as
giving True. The default for this feature is 'identity'
- 'arcsinh' - Hyperbolic arcsine feature transformer
- 'clipped_lg' - Decimal logarithm of a value clipped to a minimum
value
- 'identity' - Identity feature transformer
- 'lg' - Decimal logarithm feature transformer
- 'ln1p' - :math:`ln(1+x)` feature transformer
- 'sqrt' - Square root feature transformer
If bool, must be True to use default transformer or False to disable.
If None, no transformation is applied.
"""
features = ["InterPercentileRange"]
def __init__(self, quantile=0.25, transform=None):
self.quantile = quantile
self.transform = transform
self._extract = _InterPercentileRange(**self.params)
[docs]
@doctools.doc_inherit(LightCurveExtractor.flatten_feature)
def flatten_feature(self, feature, value):
if feature == "InterPercentileRange":
[name] = self._extract.names
percentile = name.split("_")[3]
return {f"InterPercentileRange_{percentile}": value}
return super().flatten_feature(feature, value)
