code: def pruned_c2cifft(invec, outvec, indices, pretransposed=False):
      
      N1, N2 = splay(invec)
  
      if not pretransposed:
          invec = fft_transpose(invec)
      first_phase(invec, outvec, N1=N1, N2=N2)
      out = fast_second_phase(outvec, indices, N1=N1, N2=N2)
      return out
docs: Perform a pruned iFFT, only valid for power of 2 iffts as the
      decomposition is easier to choose. This is not a strict requirement of the
      functions, but it is unlikely to the optimal to use anything but power
      of 2. (Alex to provide more details in write up.
  
      Parameters
      -----------
      invec : array
          The input vector. This should be the correlation between the data and
          the template at full sample rate. Ideally this is pre-transposed, but
          if not this will be transposed in this function.
      outvec : array
          The output of the first phase of the pruned FFT.
      indices : array of ints
          The indexes at which to calculate the full sample-rate SNR.
      pretransposed : boolean, default=False
          Used to indicate whether or not invec is pretransposed.
  
      Returns
      --------
      SNRs : array
          The complex SNRs at the indexes given by indices.