Source code for feets.extractors.ext_amplitude
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# The MIT License (MIT)
# Copyright (c) 2017 Juan Cabral
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
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# SOFTWARE.
# =============================================================================
# FUTURE
# =============================================================================
from __future__ import unicode_literals
# =============================================================================
# DOC
# =============================================================================
__doc__ = """"""
# =============================================================================
# IMPORTS
# =============================================================================
import math
import numpy as np
from .core import Extractor
# =============================================================================
# EXTRACTOR CLASS
# =============================================================================
[docs]class Amplitude(Extractor):
"""
**Amplitude**
The amplitude is defined as the half of the difference between the median
of the maximum 5% and the median of the minimum 5% magnitudes. For a
sequence of numbers from 0 to 1000 the amplitude should be equal to 475.5.
References
----------
.. [richards2011machine] Richards, J. W., Starr, D. L., Butler, N. R.,
Bloom, J. S., Brewer, J. M., Crellin-Quick, A., ... &
Rischard, M. (2011). On machine-learned classification of variable stars
with sparse and noisy time-series data.
The Astrophysical Journal, 733(1), 10. Doi:10.1088/0004-637X/733/1/10.
"""
data = ['magnitude']
features = ['Amplitude']
[docs] def fit(self, magnitude):
N = len(magnitude)
sorted_mag = np.sort(magnitude)
amplitude = (np.median(sorted_mag[-int(math.ceil(0.05 * N)):]) -
np.median(sorted_mag[0:int(math.ceil(0.05 * N))])) / 2.0
return {"Amplitude": amplitude}