text: # program fitting the exchange interaction
  # model curve: Bethe-Slater function
  import numpy as np, pylab, tkinter
  import matplotlib.pyplot as plt
  from scipy.optimize import curve_fit
  from decimal import *
  
  print("Loop begin")
  
  # definition of the Bethe-Slater function
  def func(x,a,b,c):
      return 4*a*((x/c)**2)*(1-b*(x/c)**2)*np.exp(-(x/c)**2)
  
  # exchange coeff table (data to fit)
  rdata, Jdata = np.loadtxt('exchange_fcc_ni.dat', usecols=(0,1), unpack=True)
  plt.plot(rdata, Jdata, 'b-', label='data')
  
  # perform the fit
  popt, pcov = curve_fit(func, rdata, Jdata, bounds=([0.0,-1.0,0.0], [100.,5.,5.]))
  plt.plot(rdata, func(rdata, *popt), 'r--', label='fit')
  
  # print the fitted parameters
  print("Parameters: a={:.10} (in meV), b={:.10} (adim), c={:.10} (in Ang)".format(*popt))
  
  # ploting the result
  plt.xlabel('r_ij')
  pylab.xlim([0.0,6.5])
  #pylab.ylim([-2.0,10.0])
  plt.ylabel('J_ij')
  plt.legend()
  plt.show()
  
  print("Loop end")
  