docs: def fig_lfp_corr(params, savefolders, transient=200,
                   channels=[0,3,7,11,13], Df=None,
                   mlab=True, NFFT=256, noverlap=128,
                   window=plt.mlab.window_hanning,
                   letterslist=['AB', 'CD'], data_type = 'LFP'):
      '''This figure compares power spectra for correlated and uncorrelated signals 
  
      '''
      ana_params.set_PLOS_2column_fig_style(ratio=0.5)
      fig = plt.figure()
      fig.subplots_adjust(left=0.07, right=0.95, bottom=0.1, wspace=0.3, hspace=0.1)
  
      gs = gridspec.GridSpec(5, 4)
  
  
      for i, (savefolder, letters) in enumerate(zip(savefolders, letterslist)):
          # path to simulation files
          params.savefolder = os.path.join(os.path.split(params.savefolder)[0],
                                           savefolder)
          params.figures_path = os.path.join(params.savefolder, 'figures')
          params.spike_output_path = os.path.join(params.savefolder,
                                                             'processed_nest_output')
          params.networkSimParams['spike_output_path'] = params.spike_output_path
  
  
          ## Including correlations
          f = h5py.File(os.path.join(params.savefolder, ana_params.analysis_folder, data_type + ana_params.fname_psd),'r')
          freqs = f['freqs'].value
          LFP_PSD_corr = f['psd'].value
          f.close()
      
          ## Excluding correlations
          f = h5py.File(os.path.join(params.savefolder, ana_params.analysis_folder, data_type +  ana_params.fname_psd_uncorr),'r')
          freqs = f['freqs'].value
          LFP_PSD_uncorr = f['psd'].value
          f.close()
          
       
          ##################################
          ###  Single channel LFP PSDs   ###
          ##################################
      
          ax = fig.add_subplot(gs[0, (i % 2)*2]) 
          phlp.remove_axis_junk(ax)
          ax.loglog(freqs,LFP_PSD_corr[channels[0]], color='k', label='$P$')
          ax.loglog(freqs,LFP_PSD_uncorr[channels[0]],
                    color='gray' if analysis_params.bw else analysis_params.colorP,
                    lw=1,
                    label='$\tilde{P}$')
          ax.xaxis.set_ticks_position('bottom')
          ax.yaxis.set_ticks_position('left')
          ax.text(0.80,0.82,'ch. %i' %(channels[0]+1),horizontalalignment='left',
              verticalalignment='center',
              fontsize=6, 
              transform=ax.transAxes)
          ax.yaxis.set_minor_locator(plt.NullLocator())
          ax.set_ylabel('(mV$^2$/Hz)', labelpad=0.)
          ax.set_xticks([])
          ax.set_xticklabels([])
          ax.tick_params(axis='y',which='minor',bottom='off')
          ax.set_xlim(4E0,4E2)
          ax.set_ylim(1E-8,1.5E-4)
          ax.set_yticks([1E-8,1E-6,1E-4])
          ax.set_title('power spectra')
          phlp.annotate_subplot(ax, ncols=4, nrows=5, letter=letters[0],
                             linear_offset=0.065)       
      
          ax = fig.add_subplot(gs[1, (i % 2)*2])
          phlp.remove_axis_junk(ax)
          ax.loglog(freqs,LFP_PSD_corr[channels[1]], color='k', label='corr')
          ax.loglog(freqs,LFP_PSD_uncorr[channels[1]],
                    color='gray' if analysis_params.bw else analysis_params.colorP,
                    lw=1,
                    label='uncorr')
          ax.xaxis.set_ticks_position('bottom')
          ax.yaxis.set_ticks_position('left')
          ax.text(0.80,0.82,'ch. %i' %(channels[1]+1),horizontalalignment='left',
              verticalalignment='center',
              fontsize=6, 
              transform=ax.transAxes)
          ax.yaxis.set_minor_locator(plt.NullLocator())
          ax.set_xticks([])
          ax.set_xticklabels([])
          ax.tick_params(axis='y',which='minor',bottom='off')
          ax.set_xlim(4E0,4E2)
          ax.set_ylim(1E-8,1.5E-4)
          ax.set_yticks([1E-8,1E-6,1E-4])
          ax.set_yticklabels([])
      
      
          ax = fig.add_subplot(gs[2, (i % 2)*2])
          phlp.remove_axis_junk(ax)
          ax.loglog(freqs,LFP_PSD_corr[channels[2]], color='k', label='corr')
          ax.loglog(freqs,LFP_PSD_uncorr[channels[2]],
                    color='gray' if analysis_params.bw else analysis_params.colorP,
                    lw=1,
                    label='uncorr')   
          ax.xaxis.set_ticks_position('bottom')
          ax.yaxis.set_ticks_position('left')
          ax.text(0.80,0.82,'ch. %i' %(channels[2]+1),horizontalalignment='left',
              verticalalignment='center',
              fontsize=6, 
              transform=ax.transAxes)
          ax.yaxis.set_minor_locator(plt.NullLocator())
          ax.set_xticks([])
          ax.set_xticklabels([])
          ax.tick_params(axis='y',which='minor',bottom='off')
          ax.set_xlim(4E0,4E2)
          ax.set_ylim(1E-8,1.5E-4)
          ax.set_yticks([1E-8,1E-6,1E-4])
          ax.set_yticklabels([])
      
      
          ax = fig.add_subplot(gs[3, (i % 2)*2]) 
          phlp.remove_axis_junk(ax)
          ax.loglog(freqs,LFP_PSD_corr[channels[3]], color='k', label='corr')
          ax.loglog(freqs,LFP_PSD_uncorr[channels[3]],
                    color='gray' if analysis_params.bw else analysis_params.colorP,
                    lw=1,
                    label='uncorr')   
          ax.xaxis.set_ticks_position('bottom')
          ax.yaxis.set_ticks_position('left')
          ax.text(0.80,0.82,'ch. %i' %(channels[3]+1),horizontalalignment='left',
              verticalalignment='center',
              fontsize=6, 
              transform=ax.transAxes)
          ax.yaxis.set_minor_locator(plt.NullLocator())
          ax.set_xticks([])
          ax.set_xticklabels([])
          ax.tick_params(axis='y',which='minor',bottom='off')
          ax.set_xlim(4E0,4E2)
          ax.set_ylim(1E-8,1.5E-4)
          ax.set_yticks([1E-8,1E-6,1E-4])
          ax.set_yticklabels([])
      
      
          ax = fig.add_subplot(gs[4, (i % 2)*2])
          phlp.remove_axis_junk(ax)
          ax.loglog(freqs,LFP_PSD_corr[channels[4]], color='k', label='corr')
          ax.loglog(freqs,LFP_PSD_uncorr[channels[4]],
                    color='gray' if analysis_params.bw else analysis_params.colorP,
                    lw=1,
                    label='uncorr')   
          ax.xaxis.set_ticks_position('bottom')
          ax.yaxis.set_ticks_position('left')
          ax.set_xlabel(r'$f$ (Hz)', labelpad=0.2)
          ax.text(0.80,0.82,'ch. %i' %(channels[4]+1),horizontalalignment='left',
              verticalalignment='center',
              fontsize=6, 
              transform=ax.transAxes)
          ax.yaxis.set_minor_locator(plt.NullLocator())
          ax.tick_params(axis='y',which='minor',bottom='off')
          ax.set_xlim(4E0,4E2)
          ax.set_ylim(1E-8,1.5E-4)
          ax.set_yticks([1E-8,1E-6,1E-4])
          ax.set_yticklabels([])
      
      
          ##################################
          ###  LFP PSD ratios            ###
          ##################################
      
          ax = fig.add_subplot(gs[:, (i % 2)*2 + 1]) 
          phlp.annotate_subplot(ax, ncols=4, nrows=1, letter=letters[1],
                             linear_offset=0.065)
          phlp.remove_axis_junk(ax)
          ax.set_title('power ratio')
          PSD_ratio = LFP_PSD_corr/LFP_PSD_uncorr
          
          zvec = np.r_[params.electrodeParams['z']]
          zvec = np.r_[zvec, zvec[-1] + np.diff(zvec)[-1]]
          inds = freqs >= 1  # frequencies greater than 4 Hz  
          im = ax.pcolormesh(freqs[inds], zvec+40, PSD_ratio[:, inds],
                              rasterized=False,
                              cmap=plt.get_cmap('gray_r', 12) if analysis_params.bw else plt.get_cmap('Reds', 12),
                              vmin=10**-0.25,vmax=10**2.75,norm=LogNorm())
          ax.set_xscale('log')
      
          ax.set_yticks(zvec)
          yticklabels = ['ch. %i' %i for i in np.arange(len(zvec))+1]
          ax.set_yticklabels(yticklabels)
          ax.set_xlabel(r'$f$ (Hz)',labelpad=0.2)
          plt.axis('tight')
          ax.set_xlim([4E0, 4E2])
      
          cb = phlp.colorbar(fig, ax, im,
                             width=0.05, height=0.5,
                             hoffset=-0.05, voffset=0.0)
          cb.set_label('(-)', labelpad=0.1)
  
  
   
      return fig