old_contents: '''
  Created on 28 Jun 2014
  @author: heiko, vincent
  '''
  
  # to run this script, you need to tell python where to find your code
  # 1- $gedit ~/.bashrc
  # 2- add to .bashrc the following line: export PYTHONPATH=$PYTHONPATH:path_to_repo/code/python, save, start a new terminal
  # 3- run this script: $python getting_started.py
  
   
  
  
  # Loading necessary packages
  from seizures.data.DataLoader import DataLoader
  from seizures.evaluation.XValidation import XValidation
  from seizures.evaluation.performance_measures import accuracy
  from seizures.features.ARFeatures import ARFeatures
  from seizures.prediction.ForestPredictor import ForestPredictor
  from seizures.prediction.SVMPredictor import SVMPredictor
  import sys
  
  # you can also manually declare path
  path_to_repo = "/nfs/nhome/live/vincenta/git/gatsby-hackathon-seizure/code/python/"
  sys.path.insert(1,path_to_repo)
  
  def test_predictor(predictor_cls):
      ''' function that loads data for Dog_1 run crossvalidation with ARFeatures 
          INPUT:
          - predictor_cls: a Predictor class (implement)  
      '''
  
      # instanciating a predictor object from Predictor class
      predictor = predictor_cls()    
  
      # path to data (here path from within gatsby network)
      data_path = "/nfs/data3/kaggle_seizure/"
  
      # creating instance of autoregressive features
      feature_extractor = ARFeatures()
      
      # loading the data
      loader = DataLoader(data_path, feature_extractor)
      X_list = loader.training_data("Dog_1")
      y_list = loader.labels("Dog_1")
  
      # running cross validation    
      conditioned = [a * b for (a, b) in zip(y_list[0], y_list[1])]
      print XValidation.evaluate(X_list, conditioned, predictor, evaluation=accuracy)
  
  if __name__ == '__main__':
      # code run at script launch
  
      print "ForestPredictor"
      test_predictor(ForestPredictor)
  
      print "SVMPredictor"
      test_predictor(SVMPredictor)
  
   
  
new_contents: '''
  Created on 28 Jun 2014
  @author: heiko, vincent
  '''
  
  # to run this script, you need to tell python where to find your code
  # 1- $gedit ~/.bashrc
  # 2- add to .bashrc the following line: export PYTHONPATH=$PYTHONPATH:path_to_repo/code/python, save, start a new terminal
  # 3- run this script: $python getting_started.py
  
   
  
  
  # Loading necessary packages
  
  import sys
  # you can also manually declare path
  path_to_repo = "/nfs/nhome/live/vincenta/git/gatsby-hackathon-seizure/code/python/"
  sys.path.insert(1,path_to_repo)
  
  from seizures.data.DataLoader import DataLoader
  from seizures.evaluation.XValidation import XValidation
  from seizures.evaluation.performance_measures import accuracy
  from seizures.features.ARFeatures import ARFeatures
  from seizures.prediction.ForestPredictor import ForestPredictor
  from seizures.prediction.SVMPredictor import SVMPredictor
  
  
  
  def test_predictor(predictor_cls):
      ''' function that loads data for Dog_1 run crossvalidation with ARFeatures 
          INPUT:
          - predictor_cls: a Predictor class (implement)  
      '''
  
      # instanciating a predictor object from Predictor class
      predictor = predictor_cls()    
  
      # path to data (here path from within gatsby network)
      data_path = "/nfs/data3/kaggle_seizure/"
  
      # creating instance of autoregressive features
      feature_extractor = ARFeatures()
      
      # loading the data
      loader = DataLoader(data_path, feature_extractor)
      X_list = loader.training_data("Dog_1")
      y_list = loader.labels("Dog_1")
  
      # running cross validation    
      conditioned = [a * b for (a, b) in zip(y_list[0], y_list[1])]
      print XValidation.evaluate(X_list, conditioned, predictor, evaluation=accuracy)
  
  if __name__ == '__main__':
      # code run at script launch
  
      print "ForestPredictor"
      test_predictor(ForestPredictor)
  
      print "SVMPredictor"
      test_predictor(SVMPredictor)
  
   
  
subject: fix conflict