code: import numpy as np
  import matplotlib.pyplot as plt
  import os
  
  # List separate experiments in separate folder
  # data_folders_for_separate_experiments = ['tenth_set']
  data_folders_for_separate_experiments = ['seventh_set', 'eighth_set', 'ninth_set', 'tenth_set']
  
  # For all experiments, extract the cell names
  CellNames = {}
  for experiment_folder in data_folders_for_separate_experiments:
      folder_path = './' + experiment_folder + '/'
      CellNames[experiment_folder] = [name for name in os.listdir(folder_path) if
                                      os.path.isdir(folder_path + name) and '_5HT' in name]
  CellNames['eighth_set'].remove('DRN165_5HT')  # problematic cell
  CellNames['eighth_set'].remove('DRN094_5HT')  # problematic cell
  CellNames['eighth_set'].remove('DRN156_5HT')  # problematic cell
  CellNames['seventh_set'].remove('DRN543_5HT')  # problematic cell
  CellNames['ninth_set'].remove('DRN654_5HT')  # problematic cell
  CellNames['tenth_set'].remove('DRN656_5HT')  # problematic cell
  
  
  data = np.array([[0,0,0,0,0]])
  for experiment_folder in data_folders_for_separate_experiments:
      for cell_name in CellNames[experiment_folder]:
          path_data = '../../../Dropbox/Recherches/Raphe/GIF-Ca/Results/' + cell_name + '/'
          path_results = '../../../Dropbox/Recherches/Raphe/GIF-Ca/Results/'
          data = np.concatenate((data, (np.loadtxt(path_data + 'params_IV.dat', delimiter='\n')).reshape((1,5))), axis=0)
  
  EL = data[1:,0]
  taum = data[1:,1]
  DeltaV = data[1:,2]
  V_T = data[1:,3]
  C = data[1:,4]
  
  
  
  
  
  fig = plt.figure(1, figsize=(8,3))
  #fig.suptitle('EIF model parameters for 5-HT neurons', y=0.99)
  ax1 = fig.add_subplot(141)
  ax1.tick_params(
      axis='x',          # changes apply to the x-axis
      which='both',      # both major and minor ticks are affected
      bottom='off',      # ticks along the bottom edge are off
      top='off',         # ticks along the top edge are off
      labelbottom='off') # labels along the bottom edge are off
  ax1.boxplot(EL, showmeans=True)
  plt.ylabel(r'$E_L$ (mV)')
  ax2 = fig.add_subplot(142)
  ax2.tick_params(
      axis='x',          # changes apply to the x-axis
      which='both',      # both major and minor ticks are affected
      bottom='off',      # ticks along the bottom edge are off
      top='off',         # ticks along the top edge are off
      labelbottom='off') # labels along the bottom edge are of
  plt.ylabel(r'$\tau_m$ (ms)')
  ax2.boxplot(taum, showmeans=True)
  ax3 = fig.add_subplot(143)
  ax3.tick_params(
      axis='x',          # changes apply to the x-axis
      which='both',      # both major and minor ticks are affected
      bottom='off',      # ticks along the bottom edge are off
      top='off',         # ticks along the top edge are off
      labelbottom='off') # labels along the bottom edge are off
  plt.ylabel(r'$\Delta V$ (mV)')
  ax3.boxplot(DeltaV, showmeans=True)
  ax4 = fig.add_subplot(144)
  ax4.tick_params(
      axis='x',          # changes apply to the x-axis
      which='both',      # both major and minor ticks are affected
      bottom='off',      # ticks along the bottom edge are off
      top='off',         # ticks along the top edge are off
      labelbottom='off') # labels along the bottom edge are off
  plt.ylabel(r'$V_T$ (mV)')
  ax4.boxplot(V_T, showmeans=True)
  fig.tight_layout()
  plt.savefig(path_results+'DynamicIV_Params5HT.png', format='png')
  plt.close(fig)
  
apis: matplotlib.pyplot.figure matplotlib.pyplot.savefig matplotlib.pyplot.ylabel matplotlib.pyplot.close numpy.array numpy.loadtxt