docs: def calc_signal_power(params):
  
      '''
      calculates power spectrum of sum signal for all channels
  
      '''
  
      for i, data_type in enumerate(['CSD','LFP','CSD_10_0', 'LFP_10_0']):
          if i % SIZE == RANK:
  
              # Load data
              if data_type in ['CSD','LFP']:
                  fname=os.path.join(params.savefolder, data_type+'sum.h5')
              else:
                  fname=os.path.join(params.populations_path, 'subsamples',
                                     str.split(data_type,'_')[0] + 'sum_' +
                                     str.split(data_type,'_')[1] + '_' +
                                     str.split(data_type,'_')[2] + '.h5')
              #open file
              f = h5py.File(fname)
              data = f['data'].value
              srate = f['srate'].value 
              tvec = np.arange(data.shape[1]) * 1000. / srate
          
              # slice
              slica = (tvec >= ana_params.transient)
              data = data[:,slica]
      
              # subtract mean
              dataT = data.T - data.mean(axis=1)
              data = dataT.T
              f.close()
      
              #extract PSD
              PSD=[]
              for i in np.arange(len(params.electrodeParams['z'])):
                  if ana_params.mlab:
                      Pxx, freqs=plt.mlab.psd(data[i], NFFT=ana_params.NFFT,
                                          Fs=srate, noverlap=ana_params.noverlap,
                                          window=ana_params.window)
                  else:
                      [freqs, Pxx] = hlp.powerspec([data[i]], tbin= 1.,
                                               Df=ana_params.Df, pointProcess=False)
                      mask = np.where(freqs >= 0.)
                      freqs = freqs[mask]
                      Pxx = Pxx.flatten()
                      Pxx = Pxx[mask]
                      Pxx = Pxx/tvec[tvec >= ana_params.transient].size**2
                  PSD +=[Pxx.flatten()]
                  
              PSD=np.array(PSD)
      
              # Save data
              f = h5py.File(os.path.join(params.savefolder, ana_params.analysis_folder,
                                         data_type + ana_params.fname_psd),'w')
              f['freqs']=freqs
              f['psd']=PSD
              f['transient']=ana_params.transient
              f['mlab']=ana_params.mlab
              f['NFFT']=ana_params.NFFT
              f['noverlap']=ana_params.noverlap
              f['window']=str(ana_params.window)
              f['Df']=str(ana_params.Df)
              f.close()
  
      return