Source code for feets.extractors.ext_beyond_n_std
#!/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
# =============================================================================
"""Beyond-N-standard-deviation extractor."""
# =============================================================================
# IMPORTS
# =============================================================================
from light_curve import BeyondNStd as _BeyondNStd
from .light_curve_extractor import LightCurveExtractor
from ..libs import doctools
# =============================================================================
# EXTRACTOR CLASS
# =============================================================================
[docs]
class BeyondNStd(LightCurveExtractor):
r"""Beyond-N-standard-deviation extractor.
**BeyondNStd**
Fraction of observations beyond :math:`N\,\sigma_m` from the mean
magnitude :math:`\langle m \rangle`.
.. math::
\mathrm{beyond}~n\,\sigma_m = \frac{
\sum_i I_{|m - \langle m \rangle| > n\,\sigma_m}(m_i)
}{N}
where :math:`I` is the indicator function, :math:`N` is the number of
observations, :math:`\langle m \rangle` is the mean magnitude and
:math:`\sigma_m = \sqrt{\sum_i (m_i - \langle m \rangle)^2 / (N-1)}`
is the magnitude standard deviation.
Parameters
----------
nstd : positive float, default=1
N, default is 1.0
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.
See Also
--------
feets.extractors.WeightedBeyondNStd
"""
features = ["BeyondNStd"]
def __init__(self, nstd=1, transform=None):
self.nstd = nstd
self.transform = transform
self._extract = _BeyondNStd(**self.params)
[docs]
@doctools.doc_inherit(LightCurveExtractor.flatten_feature)
def flatten_feature(self, feature, value):
if feature == "BeyondNStd":
N = self.nstd
return {f"Beyond{N}Std": value}
return super().flatten_feature(feature, value)
