old_contents: """A hello world.
  
  Uses the main libraries to verify the environment installation.
  """
  
  import sys
  
  import matplotlib.pyplot as plt
  import numpy as np
  import pydensecrf.densecrf as crf
  import pymia.evaluation.evaluator as pymia_eval
  import SimpleITK as sitk
  import sklearn.ensemble as sk_ensemble
  
  
  def main():
  
      print('Welcome to MIALab 2019!')
  
      # --- scikit-learn
      clf = sk_ensemble.RandomForestClassifier(max_depth=2, random_state=0)
  
      # --- SimpleITK
      image = sitk.Image(256, 128, 64, sitk.sitkInt16)
      print('Image dimension:', image.GetDimension())
      print('Voxel intensity before setting:', image.GetPixel(0, 0, 0))
      image.SetPixel(0, 0, 0, 1)
      print('Voxel intensity after setting:', image.GetPixel(0, 0, 0))
  
      # --- numpy and matplotlib
      array = np.array([1, 23, 2, 4])
      plt.plot(array)
      plt.ylabel('Some meaningful numbers')
      plt.xlabel('The x-axis')
      plt.title('Wohoo')
  
      plt.show()
  
      # --- pydensecrf
      d = crf.DenseCRF(1000, 2)
  
      # --- pymia
      eval = pymia_eval.Evaluator()
  
      print('Everything seems to work fine!')
  
  
  if __name__ == "__main__":
      """The program's entry point."""
  
      main()
  
new_contents: """A hello world.
  
  Uses the main libraries to verify the environment installation.
  """
  
  import sys
  
  import matplotlib.pyplot as plt
  import numpy as np
  # import pydensecrf.densecrf as crf
  import pymia.evaluation.evaluator as pymia_eval
  import SimpleITK as sitk
  import sklearn.ensemble as sk_ensemble
  
  
  def main():
  
      print('Welcome to MIALab 2019!')
  
      # --- scikit-learn
      clf = sk_ensemble.RandomForestClassifier(max_depth=2, random_state=0)
  
      # --- SimpleITK
      image = sitk.Image(256, 128, 64, sitk.sitkInt16)
      print('Image dimension:', image.GetDimension())
      print('Voxel intensity before setting:', image.GetPixel(0, 0, 0))
      image.SetPixel(0, 0, 0, 1)
      print('Voxel intensity after setting:', image.GetPixel(0, 0, 0))
  
      # --- numpy and matplotlib
      array = np.array([1, 23, 2, 4])
      plt.plot(array)
      plt.ylabel('Some meaningful numbers')
      plt.xlabel('The x-axis')
      plt.title('Wohoo')
  
      plt.show()
  
      # --- pydensecrf
      # d = crf.DenseCRF(1000, 2)
  
      # --- pymia
      eval = pymia_eval.Evaluator()
  
      print('Everything seems to work fine!')
  
  
  if __name__ == "__main__":
      """The program's entry point."""
  
      main()
  
subject: remove CRF