old_contents: #!/usr/bin/env python
  # coding : utf-8
  
  """
  Main module for VOI analyzer.
  """
  
  import pandas as pd
  import numpy as np
  import argparse
  import os
  
  
  
  
new_contents: #!/usr/bin/env python
  # coding : utf-8
  
  """
  Main module for VOI analyzer.
  """
  
  import pandas as pd
  import numpy as np
  import argparse
  import os
  
  def _analysis(img_mat, voi_mat, voi_no, eps=1e-12):
      """ Extract VOI statistices for each VOI.
      """
      vec = img_mat[voi_mat == voi_no]
      vec2 = vec[~np.isnan(vec)]
  
      # Statistics
      v_mean = float(vec2.mean())
      v_sd = float(vec2.std(ddof=1))
      v_cov = v_sd / (v_mean + eps) * 100.
      v_max = float(vec2.max())
      v_min = float(vec2.min())
      n_vox = vec.size
  
      # Output
      out_tab = pd.DataFrame({"VOI No." :  [voi_no],
                              "No. of voxels" : [n_vox],
                              "Mean" : [v_mean],
                              "SD" : [v_sd],
                              "CoV" : [v_cov],
                              "Max" : [v_max],
                              "Min" : [v_min]})
  
      return out_tab
  
  def voi_analysis(img_file, voi_file, lut_file=None):
      """ Extract VOI values.
      It outputs Pandas DataFrame for VOI statistics.
  
      Inputs:
          img_file   :    Path for image to extract VOI values
  
          voi_file    :   Path for VOI map
  
          lut_file    :   Path for look-up table for VOI map.
                          If not None, look-up table is applied to output table.
  
      Output:
          out_tab     :   Pandas DataFrame for VOI statistics.
      """
      # Load image & VOI
      img_mat, img_aff = utils.loadImage(img_file)[:2]
      voi_mat = utils.loadImage(voi_file)[0].astype(np.int16)
      
      # Extract
      maxNo = voi_mat.max()
      out_tab = pd.concat([_analysis(img_mat, voi_mat, v_no)
                              for v_no in range(1, maxNo + 1, 1)])
  
      # Calculate volumes (unit: cm3)
      vol_per_vox = np.abs(np.prod(np.diag(img_aff[:3, :3])))
      out_tab.loc[:, "Volume"] = out_tab.loc[:, "No. of voxels"] / 1000.
  
      # Apply look-up table
      if lut_file is not None:
          lut = utils.loadLUT(lut_file)
          out_tab.loc[:, "VOI"] = out_tab.loc[:, "VOI No."].map(lut)
  
      # Image file name
      out_tab.loc[:, "Path"] = img_file
  
      return out_tab
  
  
subject: Implement basis for VOI analyzer.