docs: def gp_norm(infile):
      """indentify normalization region"""
      inDir, outDir = getWorkDirs()
      data, titles = [], []
      for eidx,energy in enumerate(['19', '27', '39', '62']):
          file_url = os.path.realpath(os.path.join(
              inDir, 'rawdata', energy, 'pt-integrated', infile+'.dat'
          ))
          data_import = np.loadtxt(open(file_url, 'rb'))
          data_import[:,1] += eidx * 0.2
          data_import[:,4] = data_import[:,3]
          data_import[:,(2,3)] = 0
          data.append(data_import)
          titles.append(' '.join([getEnergy4Key(energy), 'GeV']))
      nData = len(data)
      lines = dict(
          ('x={}'.format(1+i*0.2), 'lc {} lt 2 lw 4'.format(default_colors[-2]))
          for i in range(nData)
      )
      lines.update(dict(
          ('x={}'.format(1+i*0.2+0.02), 'lc {} lt 3 lw 4'.format(default_colors[-5]))
          for i in range(nData)
      ))
      lines.update(dict(
          ('x={}'.format(1+i*0.2-0.02), 'lc {} lt 3 lw 4'.format(default_colors[-5]))
          for i in range(nData)
      ))
      lines.update({'y=0.9': 'lc {} lt 1 lw 4'.format(default_colors[-2])})
      charges = '++' if infile == 'rpp' else '--'
      make_plot(
          name = '%s/norm_range_%s' % (outDir,infile), xr = [0,2], yr = [0.9,1.7],
          data = data, properties = [
              'lt 1 lw 3 lc %s pt 1' % (default_colors[i]) # (i/2)%4
              for i in range(nData)
          ], titles = titles, size = '8in,8in',
          lmargin = 0.05, rmargin = 0.99, tmargin = 0.93, bmargin = 0.14,
          xlabel = 'dielectron invariant mass, M_{ee} (GeV/c^{2})',
          lines = lines, key = [
              'maxrows 1', 'nobox', 'samplen 0.1', 'width -1', 'at graph 1,1.1'
          ], labels = {
              'SE_{%s} / ME@_{%s}^N' % (charges, charges): (0.3, 1.3)
          }, gpcalls = [
              'ytics (1,"1" 1.2, "1" 1.4, "1" 1.6)', 'boxwidth 0.002',
          ],
      )