Source code for feets.extractors.ext_time_std
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2017-2024, Cabral, Juan
# Copyright (c) 2025, QuatroPe; ClariĆ”, Felipe
# License: MIT
# Full Text:
# https://github.com/quatrope/feets/blob/master/LICENSE
# =============================================================================
# DOC
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"""Time standard deviation extractor."""
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# IMPORTS
# =============================================================================
from light_curve import TimeStandardDeviation as _TimeStandardDeviation
from .light_curve_extractor import LightCurveExtractor
from ..libs import doctools
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# EXTRACTOR CLASS
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[docs]
class TimeStd(LightCurveExtractor):
r"""Standard deviation of time moments.
**TimeStd** (:math:`\sigma_t`)
.. math::
\sigma_t = \frac{\sum_i {(t_i - \langle t \rangle)^2}}{N - 1}
where :math:`N` is the number of observations and :math:`\langle m \rangle`
is the mean magnitude.
Parameters
----------
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 = ["TimeStd"]
def __init__(self, transform=None):
self.transform = transform
self._extract = _TimeStandardDeviation(**self.params)