old_contents: import numpy as np
  
  __all__ = ['LightCurve']
  
  class LightCurve(object):
      """
      Implements a basic time-series class for a generic lightcurve.
  
      Parameters
      ----------
      time : numpy array-like
          Time-line.
      flux : numpy array-like
          Data flux for every time point.
      """
  
      def __init__(self, time, flux):
          self.time = time
          self.flux = flux
  
      def detrend(self, method='arclength', **kwargs):
          """
          """
          if method == 'arclength':
              return ArcLengthDetrender().detrend(self.time, self.flux, **kwargs)
          else:
              return FirstDifferenceDetrender().detrend(self.time, self.flux, **kwargs)
  
      def to_pandas(self):
          raise NotImplementedError("@gully")
  
  class Detrender(object):
      """
      """
      def detrend(self):
          """
          Returns a LightCurve object
          """
          pass
  
  class SystematicsCorrector(object):
      """
      """
      def correct(**kwargs):
          """
          """
          pass
  
  class FirstDifferenceDetrender(Detrender):
      """
      First difference detrending
      """
      def detrend(time, flux):
          return LightCurve(time, flux - np.append(0, flux[1:]))
  
  class LinearDetrender(Detrender):
      """
      """
      @staticmethod
      def detrend(time, flux):
          pass
  
  class ArcLengthDetrender(Detrender):
      def detrend(time, flux):
          pass
  
  class EMDDetrender(Detrender):
      """
      Empirical Mode Decomposition Detrender
      """
      def detrend(time, flux):
          pass
  
  class PolynomialDetrender(Detrender):
      """
      """
      def detrend(time, flux):
          pass
  
new_contents: import numpy as np
  
  __all__ = ['LightCurve']
  
  class LightCurve(object):
      """
      Implements a basic time-series class for a generic lightcurve.
  
      Parameters
      ----------
      time : numpy array-like
          Time-line.
      flux : numpy array-like
          Data flux for every time point.
      """
  
      def __init__(self, time, flux):
          self.time = time
          self.flux = flux
  
      def detrend(self, method='arclength', **kwargs):
          """
          """
          if method == 'arclength':
              return ArcLengthDetrender().detrend(self.time, self.flux, **kwargs)
          else:
              return FirstDifferenceDetrender().detrend(self.time, self.flux, **kwargs)
  
      def to_pandas(self):
          raise NotImplementedError("@gully")
  
  class Detrender(object):
      """
      """
      def detrend(self):
          """
          Returns a LightCurve object
          """
          pass
  
  class FirstDifferenceDetrender(Detrender):
      """
      First difference detrending
      """
      def detrend(time, flux):
          return LightCurve(time, flux - np.append(0, flux[1:]))
  
  class LinearDetrender(Detrender):
      """
      """
      @staticmethod
      def detrend(time, flux):
          pass
  
  class ArcLengthDetrender(Detrender):
      def detrend(time, flux):
          pass
  
  class EMDDetrender(Detrender):
      """
      Empirical Mode Decomposition Detrender
      """
      def detrend(time, flux):
          pass
  
  class PolynomialDetrender(Detrender):
      """
      """
      def detrend(time, flux):
          pass
  
subject: remove SystematicsCorrector class