old_contents: # -*- coding: utf-8 -*-
  """ Envelope-to-Signal Correlation
  
  
  Proposed by Bruns and Eckhorn [Bruns2004_], Envelope-to-Signal Correlation (*ESC*)
  is similar to Amplitude Envelope Correlation (:mod:`dyfunconn.fc.aec`), but the
  the amplitude of the lower frequency oscillation is signed; and thus the phase
  information is preserved.
  
  .. math::
      r_{ESC} = \\text{corr}(\\chi_{lo}, \\alpha_{hi})
  
  Where :math:`\\chi` is the input signal filtered to the frequency band :math:`lo`
  and :math:`\\alpha` denotes the Instantaneous Amplitude of the same input signal
  at the frequency band :math:`hi`.
  
  |
  
  -----
  
  
  .. [Penny2008] Penny, W. D., Duzel, E., Miller, K. J., & Ojemann, J. G. (2008). Testing for nested oscillation. Journal of neuroscience methods, 174(1), 50-61. Chicago
  .. [Bruns2004] Bruns, A., & Eckhorn, R. (2004). Task-related coupling from high-to low-frequency signals among visual cortical areas in human subdural recordings. International Journal of Psychophysiology, 51(2), 97-116.
  """
  # Author: Avraam Marimpis <avraam.marimpis@gmail.com>
  
  from ..analytic_signal import analytic_signal
  
  import numpy as np
  
  
  def esc(data, fb_lo, fb_hi, fs):
      """ Envelope-Signal-Correlation
  
      Estimate the Envelope-Signal-Correlation the given :attr:`data`.
  
  
      Parameters
      ----------
      data : array-like, shape(n_channels, n_samples)
          Multichannel recording data.
  
      fb_lo : list of length 2
          The low and high frequencies of the lower band.
  
      fb_hi : list of length 2
          The low and high frequencies of the upper band.
  
      fs : float
          Sampling frequency.
  
      pairs : array-like or `None`
          - If an `array-like` is given, notice that each element is a tuple of length two.
          - If `None` is passed, complete connectivity will be assumed.
  
  
      Returns
      -------
      r : array-like, shape(n_channels, n_channels)
          Estimated Pearson correlation coefficient.
      """
      f, _, _ = analytic_signal(data, fb_lo, fs)
      _, h, _ = analytic_signal(data, fb_hi, fs)
  
      escv = np.corrcoef(f, np.abs(h))
      escv = np.float32(escv)
  
      return escv
  
new_contents: # -*- coding: utf-8 -*-
  """ Envelope-to-Signal Correlation
  
  
  Proposed by Bruns and Eckhorn [Bruns2004_], Envelope-to-Signal Correlation (*ESC*)
  is similar to Amplitude Envelope Correlation (:mod:`dyfunconn.fc.aec`), but the
  the amplitude of the lower frequency oscillation is signed; and thus the phase
  information is preserved.
  
  .. math::
      r_{ESC} = \\text{corr}(\\chi_{lo}, \\alpha_{hi})
  
  Where :math:`\\chi` is the input signal filtered to the frequency band :math:`lo`
  and :math:`\\alpha` denotes the Instantaneous Amplitude of the same input signal
  at the frequency band :math:`hi`.
  
  |
  
  -----
  
  .. [Bruns2004] Bruns, A., & Eckhorn, R. (2004). Task-related coupling from high-to low-frequency signals among visual cortical areas in human subdural recordings. International Journal of Psychophysiology, 51(2), 97-116.
  .. [Penny2008] Penny, W. D., Duzel, E., Miller, K. J., & Ojemann, J. G. (2008). Testing for nested oscillation. Journal of neuroscience methods, 174(1), 50-61. Chicago
  """
  # Author: Avraam Marimpis <avraam.marimpis@gmail.com>
  
  from ..analytic_signal import analytic_signal
  
  import numpy as np
  
  
  def esc(data, fb_lo, fb_hi, fs):
      """ Envelope-Signal-Correlation
  
      Estimate the Envelope-Signal-Correlation the given :attr:`data`.
  
  
      Parameters
      ----------
      data : array-like, shape(n_channels, n_samples)
          Multichannel recording data.
  
      fb_lo : list of length 2
          The low and high frequencies of the lower band.
  
      fb_hi : list of length 2
          The low and high frequencies of the upper band.
  
      fs : float
          Sampling frequency.
  
      pairs : array-like or `None`
          - If an `array-like` is given, notice that each element is a tuple of length two.
          - If `None` is passed, complete connectivity will be assumed.
  
  
      Returns
      -------
      r : array-like, shape(n_channels, n_channels)
          Estimated Pearson correlation coefficient.
      """
      f, _, _ = analytic_signal(data, fb_lo, fs)
      _, h, _ = analytic_signal(data, fb_hi, fs)
  
      escv = np.corrcoef(f, np.abs(h))
      escv = np.float32(escv)
  
      return escv
  
subject: Update citation.