docs: def plot_signal_sum_colorplot(ax, params, fname='LFPsum.h5', unit='mV', N=1, ylabels = True,
                                T=[800, 1000], ylim=[-1500, 0], fancy=False, colorbar=True,
                                cmap='spectral_r', absmax=None, transient=200, rasterized=True):
      '''
      on colorplot and as background plot the summed CSD contributions
      
      args:
      ::
          ax : matplotlib.axes.AxesSubplot object
          T : list, [tstart, tstop], which timeinterval
          ylims : list, set range of yaxis to scale with other plots
          fancy : bool, 
          N : integer, set to number of LFP generators in order to get the normalized signal
      '''
      f = h5py.File(fname)
      data = f['data'].value
      tvec = np.arange(data.shape[1]) * 1000. / f['srate'].value
      
      #for mean subtraction
      datameanaxis1 = f['data'].value[:, tvec >= transient].mean(axis=1)
      
      # slice
      slica = (tvec <= T[1]) & (tvec >= T[0])
      data = data[:,slica]
  
      # subtract mean
      #dataT = data.T - data.mean(axis=1)
      dataT = data.T - datameanaxis1
      data = dataT.T
  
      # normalize
      data = data/N
      zvec = params.electrodeParams['z']
      
      if fancy:
          colors = phlp.get_colors(data.shape[0])
      else:
          colors = ['k']*data.shape[0]
      
      if absmax == None:
          absmax=abs(np.array([data.max(), data.min()])).max()  
      im = ax.pcolormesh(tvec[slica], np.r_[zvec, zvec[-1] + np.diff(zvec)[-1]] + 50, data,
                             rasterized=rasterized, vmax=absmax, vmin=-absmax, cmap=cmap)
      ax.set_yticks(params.electrodeParams['z'])
      if ylabels:
          yticklabels = ['ch. %i' %(i+1) for i in np.arange(len(params.electrodeParams['z']))]
          ax.set_yticklabels(yticklabels)
      else:
          ax.set_yticklabels([])
  
      if colorbar:
          #colorbar
          divider=make_axes_locatable(ax)
          cax=divider.append_axes("right", size="5%", pad=0.1)
          cbar=plt.colorbar(im, cax=cax)
          cbar.set_label(unit,labelpad=0.1)
          
      plt.axis('tight')
  
      ax.set_ylim(ylim)
  
      
      f.close()
      
      return im