code: def traceback_plot(self,fsize=(6,4)):
          
          traceback_states = self.paths.traceback_states
          plt.figure(figsize=fsize)
          plt.axis([-self.decision_depth+1, 0, 
                    -(self.Nstates-1)-0.5, 0.5])
          M,N = traceback_states.shape
          traceback_states = -traceback_states[:,::-1]
  
          plt.plot(range(-(N-1),0+1),traceback_states.T)
          plt.xlabel('Traceback Symbol Periods')
          plt.ylabel('State Index $0$ to -$2^{(K-1)}$')
          plt.title('Survivor Paths Traced Back From All %d States' % self.Nstates)
          plt.grid()
docs: Plots a path of the possible last 4 states.
  
          Parameters
          ----------
          fsize : Plot size for matplotlib.
  
          Examples
          --------
          >>> import matplotlib.pyplot as plt
          >>> from sk_dsp_comm.fec_conv import fec_conv
          >>> from sk_dsp_comm import digitalcom as dc
          >>> import numpy as np
          >>> cc = fec_conv()
          >>> x = np.random.randint(0,2,100)
          >>> state = '00'
          >>> y,state = cc.conv_encoder(x,state)
          >>> # Add channel noise to bits translated to +1/-1
          >>> yn = dc.cpx_AWGN(2*y-1,5,1) # SNR = 5 dB
          >>> # Translate noisy +1/-1 bits to soft values on [0,7]
          >>> yn = (yn.real+1)/2*7
          >>> z = cc.viterbi_decoder(yn)
          >>> cc.traceback_plot()
          >>> plt.show()