old_contents: 
  import numpy as np
  
  
  def gcc_phat(sig, refsig, fs=1, max_tau=None, interp=16):
      '''
      This function computes the offset between the signal sig and the reference signal refsig
      using the Generalized Cross Correlation - Phase Transform (GCC-PHAT)method.
      '''
      
      # make sure the length for the FFT is larger or equal than len(sig) + len(refsig)
      n = sig.shape[0] + refsig.shape[0]
  
      # Generalized Cross Correlation Phase Transform
      SIG = np.fft.rfft(sig, n=n)
      REFSIG = np.fft.rfft(refsig, n=n)
      R = SIG * np.conj(REFSIG)
  
      cc = np.fft.irfft(R / np.abs(R), n=(interp * n))
  
      if not max_tau:
          max_tau = n / 2.0
  
      max_shift = int(interp * fs * max_tau)
  
      cc = np.concatenate((cc[-max_shift:], cc[:max_shift+1]))
  
      # find max cross correlation index
      shift = np.argmax(np.abs(cc))
      tau = (shift - max_shift) / float(interp * fs)
      
      return tau
  
  
  def main():
      
      refsig = np.linspace(1, 10, 10)
  
      for i in range(0, 10):
          sig = np.concatenate((np.linspace(0, 0, i), refsig, np.linspace(0, 0, 10 - i)))
          print(gcc_phat(sig, refsig))
  
      
  if __name__ == "__main__":
      main()
  
  
  
  
  
new_contents: """
   Estimate time delay using GCC-PHAT 
   Copyright (c) 2017 Yihui Xiong
  
   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at
  
       http://www.apache.org/licenses/LICENSE-2.0
  
   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.
  """
  
  import numpy as np
  
  
  def gcc_phat(sig, refsig, fs=1, max_tau=None, interp=16):
      '''
      This function computes the offset between the signal sig and the reference signal refsig
      using the Generalized Cross Correlation - Phase Transform (GCC-PHAT)method.
      '''
      
      # make sure the length for the FFT is larger or equal than len(sig) + len(refsig)
      n = sig.shape[0] + refsig.shape[0]
  
      # Generalized Cross Correlation Phase Transform
      SIG = np.fft.rfft(sig, n=n)
      REFSIG = np.fft.rfft(refsig, n=n)
      R = SIG * np.conj(REFSIG)
  
      cc = np.fft.irfft(R / np.abs(R), n=(interp * n))
  
      if not max_tau:
          max_tau = n / 2.0
  
      max_shift = int(interp * fs * max_tau)
  
      cc = np.concatenate((cc[-max_shift:], cc[:max_shift+1]))
  
      # find max cross correlation index
      shift = np.argmax(np.abs(cc))
      tau = (shift - max_shift) / float(interp * fs)
      
      return tau
  
  
  def main():
      
      refsig = np.linspace(1, 10, 10)
  
      for i in range(0, 10):
          sig = np.concatenate((np.linspace(0, 0, i), refsig, np.linspace(0, 0, 10 - i)))
          print(gcc_phat(sig, refsig))
  
      
  if __name__ == "__main__":
      main()
  
  
  
  
  
subject: add header