old_contents: from tcga_encoder.utils.helpers import *
  #from tcga_encoder.data.data import *
  #from tcga_encoder.definitions.tcga import *
  #from tcga_encoder.definitions.nn import *
  from tcga_encoder.definitions.locations import *
  import pdb
  import sys
  import tcga_encoder.models.survival.main_model_selection as runner
  
  def replace_template(template, disease_group ):
    
    disease_group = disease_group.rstrip('\n')
    disease_list = disease_group.split(" ")
    
    y = load_yaml( template )
    
    y['data']['validation_tissues'] = []
    if disease_list.__class__ == list:
      y['data']['validation_tissues'] = disease_list
      diseases = disease_list[0] 
      for d in disease_list[1:]:
        diseases += "_%s"%(d) 
        
    else:
      y['data']['validation_tissues'] = [disease_list]
      diseases = disease_list
    
    y['logging']['experiment'] += diseases
    
    this_yaml = template.rstrip(".yaml") + "_runner.yaml"
    #template
    with open(this_yaml, 'w') as yaml_file:
      yaml.dump(y, yaml_file, default_flow_style=False)
        
    #pdb.set_trace()
    return this_yaml
  
  
  if __name__ == "__main__":
    assert len(sys.argv) >= 2, "Must pass yaml file."
    yaml_template_file = sys.argv[1]
    disease_list_file = sys.argv[2]
    print "Running template: ",yaml_template_file
    
    disease_list = open( disease_list_file, "r" ).readlines()
    weights_matrix = []
  
    diseases = []
    for disease_group in disease_list:
      print "Running disease_group = %s"%(disease_group)
      diseases.append( disease_group.rstrip("\n"))
      yaml_file = replace_template( yaml_template_file, disease_group )
      runner.main( yaml_file, weights_matrix )
      #weights.append( yaml_file["weights"] )
    
    #pdb.set_trace()
    # weights_matrix = np.array(weights_matrix)
    # columns = ["z%d"%z for z in range(weights_matrix.shape[1])]
    # df = pd.DataFrame( weights_matrix, columns = columns, index = diseases )
    # y = load_yaml( yaml_template_file )
    # logging_dict   = y[LOGGING]
    # logging_dict[SAVEDIR] = os.path.join( HOME_DIR, logging_dict[LOCATION]  )
    # w_location = os.path.join( logging_dict[SAVEDIR], "weights.csv" )
    # df.to_csv( w_location)
    # print df
      #break
  
    
    
    
new_contents: from tcga_encoder.utils.helpers import *
  #from tcga_encoder.data.data import *
  #from tcga_encoder.definitions.tcga import *
  #from tcga_encoder.definitions.nn import *
  from tcga_encoder.definitions.locations import *
  import pdb
  import sys
  import tcga_encoder.models.survival.main_xval_x_to_z_model_selection as runner
  
  def replace_template(template, disease_group ):
    
    disease_group = disease_group.rstrip('\n')
    disease_list = disease_group.split(" ")
    
    y = load_yaml( template )
    
    y['data']['validation_tissues'] = []
    if disease_list.__class__ == list:
      y['data']['validation_tissues'] = disease_list
      diseases = disease_list[0] 
      for d in disease_list[1:]:
        diseases += "_%s"%(d) 
        
    else:
      y['data']['validation_tissues'] = [disease_list]
      diseases = disease_list
    
    y['logging']['experiment'] += diseases
    
    this_yaml = template.rstrip(".yaml") + "_runner.yaml"
    #template
    with open(this_yaml, 'w') as yaml_file:
      yaml.dump(y, yaml_file, default_flow_style=False)
        
    #pdb.set_trace()
    return this_yaml
  
  
  if __name__ == "__main__":
    assert len(sys.argv) >= 2, "Must pass yaml file."
    yaml_template_file = sys.argv[1]
    disease_list_file = sys.argv[2]
    print "Running template: ",yaml_template_file
    
    disease_list = open( disease_list_file, "r" ).readlines()
    weights_matrix = []
  
    diseases = []
    for disease_group in disease_list:
      print "Running disease_group = %s"%(disease_group)
      diseases.append( disease_group.rstrip("\n"))
      yaml_file = replace_template( yaml_template_file, disease_group )
      runner.main( yaml_file, weights_matrix )
      #weights.append( yaml_file["weights"] )
    
    #pdb.set_trace()
    # weights_matrix = np.array(weights_matrix)
    # columns = ["z%d"%z for z in range(weights_matrix.shape[1])]
    # df = pd.DataFrame( weights_matrix, columns = columns, index = diseases )
    # y = load_yaml( yaml_template_file )
    # logging_dict   = y[LOGGING]
    # logging_dict[SAVEDIR] = os.path.join( HOME_DIR, logging_dict[LOCATION]  )
    # w_location = os.path.join( logging_dict[SAVEDIR], "weights.csv" )
    # df.to_csv( w_location)
    # print df
      #break
  
    
    
    
subject: correct main