text: import random as rand
  import matplotlib.pyplot as plt
  import numpy as np
  
  for i in range(20, 100001):
      a0 = rand.uniform(-10000, 10000)
      a1 = rand.uniform(-10000, 10000)
      a2 = rand.uniform(-10000, 10000)
      a3 = rand.uniform(-10000, 10000)
      a4 = rand.uniform(-10000, 10000)
      a5 = rand.uniform(-10000, 10000)
      #a6 = rand.uniform(-10000, 10000)
      #a7 = rand.uniform(-10000, 10000)
      
      b0 = rand.uniform(-10000, 10000)
      b1 = rand.uniform(-10000, 10000)
      b2 = rand.uniform(-10000, 10000)
      b3 = rand.uniform(-10000, 10000)
      b4 = rand.uniform(-10000, 10000)
      b5 = rand.uniform(-10000, 10000)
      #b6 = rand.uniform(-10000, 10000)
      #b7 = rand.uniform(-10000, 10000)
      
      A = lambda x: a0 + a1*x + a2*x**2 + a3*x**3 + a4*x**4 + a5*x**5 #+ a6*x**6 + a7*x**7
      B = lambda x: b0 + b1*x + b2*x**2 + b3*x**3 + b4*x**4 + b5*x**5 #+ b6*x**6 + b7*x**7
      
      arr = []
      for x in np.arange(-150, 150, 1):   # 300 points for each test
          arr.append( [x, A(x) / B(x)] )
      x_noise = rand.uniform(-100, 100) / 1000
      y_noise = rand.uniform(-100, 100) / 1000
  
      file_name = '../in/in_{}.txt'.format(i)
      with open(file_name, 'w+') as _in:	
          for j in range(len(arr)):
              _in.write(str(arr[j][0] + x_noise))
              _in.write(';')
              _in.write(str(arr[j][1] + y_noise))
              _in.write('\n')
  