content: import scipy as sp
  import sys, os
  try:
      import libmr
      print("Imported libmr succesfully")
  except ImportError:
      print("Cannot import libmr")
      sys.exit()
  
  import pickle
  svm_data = {}
  svm_data["labels"] = [1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1,
                        1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1,
                        1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1,
                        1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1,
                        1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1]
  svm_data["scores"] = sp.randn(100).tolist()
  fit_data = sp.rand(3)
  def main():
  
      mr = libmr.MR()
      datasize = len(svm_data["scores"])
      mr.fit_svm(svm_data, datasize, 1, 1, 1, 10)
      print(fit_data)
      print(mr.w_score_vector(fit_data))
      mr.mr_save("meta_rec.model")
      datadump = {}
      datadump = {"data": fit_data}
  
      f = open("data.dump", "w")
      pickle.dump(datadump, f)
      f.close()
      print(dir(mr))
  
  
  if __name__ == "__main__":
      main()
  