code: def scatter(x,Ns,start):
      
      xI = np.real(x[start::Ns])
      xQ = np.imag(x[start::Ns])
      return xI, xQ
docs: Sample a baseband digital communications waveform at the symbol spacing.
  
      Parameters
      ----------
      x : ndarray of the input digital comm signal
      Ns : number of samples per symbol (bit)
      start : the array index to start the sampling
  
      Returns
      -------
      xI : ndarray of the real part of x following sampling
      xQ : ndarray of the imaginary part of x following sampling
  
      Notes
      -----
      Normally the signal is complex, so the scatter plot contains 
      clusters at point  in the complex plane. For a binary signal 
      such as BPSK, the point centers are nominally +/-1 on the real
      axis. Start is used to eliminate transients from the FIR
      pulse shaping filters from appearing in the scatter plot.
  
      Examples
      --------
      >>> import matplotlib.pyplot as plt
      >>> from sk_dsp_comm import digitalcom as dc
      >>> x,b, data = dc.NRZ_bits(1000,10,'rc')
  
      Add some noise so points are now scattered about +/-1.
  
      >>> y = dc.cpx_AWGN(x,20,10)
      >>> yI,yQ = dc.scatter(y,10,60)
      >>> plt.plot(yI,yQ,'.')
      >>> plt.grid()
      >>> plt.xlabel('In-Phase')
      >>> plt.ylabel('Quadrature')
      >>> plt.axis('equal')
      >>> plt.show()