text: 
  import matplotlib.pyplot as plt
  import numpy as np
  from load_data import get_data
  from Codes import k_cross_validation
  import os
  
  DATA_NAME = "concentric_circle"
  traindata, trainlabel, testdata, testlabel = get_data(DATA_NAME)
  FOLD_NO = 5
  
  INITIAL_NEURAL_ACTIVITY = [0.21]
  DISCRIMINATION_THRESHOLD = [0.96]
  EPSILON = np.arange(0.001, 1.001, 0.001)
  FSCORE, Q, B, EPS, EPSILON = k_cross_validation(FOLD_NO, traindata, trainlabel, testdata, testlabel, INITIAL_NEURAL_ACTIVITY, DISCRIMINATION_THRESHOLD, EPSILON, DATA_NAME)
  
  
  PATH = os.getcwd()
  RESULT_PATH = PATH + '/SR-PLOTS/' + DATA_NAME + '/NEUROCHAOS-RESULTS/'
  plt.figure(figsize=(10,10))
  plt.plot(EPSILON,FSCORE[0,0,:],'-*k', markersize = 10)
  plt.xticks(fontsize=20)
  plt.yticks(fontsize=20)
  plt.grid(True)
  plt.xlabel('Noise intensity', fontsize=20)
  plt.ylabel('Average F1-score', fontsize=20)
  plt.ylim(0, 1)
  plt.tight_layout()
  plt.savefig(RESULT_PATH+"/Chaosnet-"+DATA_NAME+"-SR_plot.jpg", format='jpg', dpi=200)
  plt.show()
      