text: #!/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
  # in the Software without restriction, including without limitation the rights
  # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  # copies of the Software, and to permit persons to whom the Software is
  # furnished to do so, subject to the following conditions:
  
  # The above copyright notice and this permission notice shall be included in
  # all copies or substantial portions of the Software.
  
  # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  # SOFTWARE.
  
  
  # =============================================================================
  # FUTURE
  # =============================================================================
  
  from __future__ import unicode_literals
  
  
  # =============================================================================
  # DOC
  # =============================================================================
  
  __doc__ = """"""
  
  
  # =============================================================================
  # IMPORTS
  # =============================================================================
  
  import numpy as np
  
  from .core import Extractor
  
  
  # =============================================================================
  # EXTRACTOR CLASS
  # =============================================================================
  
  class RCS(Extractor):
      r"""
      **Rcs** - Range of cumulative sum (:math:`R_{cs}`)
  
      :math:`R_{cs}` is the range of a cumulative sum (Ellaway 1978) of each
      light-curve and is defined as:
  
      .. math::
  
          R_{cs} = max(S) - min(S) \\
          S = \frac{1}{N \sigma} \sum_{i=1}^l (m_i - \bar{m})
  
      where max(min) is the maximum (minimum) value of S and
      :math:`l=1,2, \dots, N`.
  
      :math:`R_{cs}` should take a value close to zero for any symmetric
      distribution:
  
      .. code-block:: pycon
  
          >>> fs = feets.FeatureSpace(only=['Rcs'])
          >>> features, values = fs.extract(**lc_normal)
          >>> dict(zip(features, values))
          {'Rcs': 0.0094459606901065168}
  
      References
      ----------
  
      .. [kim2011quasi] Kim, D. W., Protopapas, P., Byun, Y. I., Alcock, C.,
         Khardon, R., & Trichas, M. (2011). Quasi-stellar object selection
         algorithm using time variability and machine learning: Selection of
         1620 quasi-stellar object candidates from MACHO Large Magellanic Cloud
         database. The Astrophysical Journal, 735(2), 68.
         Doi:10.1088/0004-637X/735/2/68.
  
      """
  
      data = ['magnitude']
      features = ['Rcs']
  
      def fit(self, magnitude):
          sigma = np.std(magnitude)
          N = len(magnitude)
          m = np.mean(magnitude)
          s = np.cumsum(magnitude - m) * 1.0 / (N * sigma)
          R = np.max(s) - np.min(s)
          return {"Rcs": R}
  