new_contents: # -*- coding: utf-8 -*-
  
  """Script which can be used to compare the features obtained of two different influenza models
  
  Usage:
    get_model_statistics.py <model> [--country=<country_name>] [--no-future] [--basedir=<directory>] [--start-year=<start_year>] [--end-year=<end_year>] [--save] [--no-graph]
  
    <baseline>      Data file of the first model
    <other_method>     Data file of the second model
    -h, --help        Print this help message
  """
  
  import pandas as pd
  from scipy import stats
  from docopt import docopt
  import os
  import glob
  
  def get_results_filename(basepath):
      files = [f for f in glob.glob(basepath + "/*-prediction.csv", recursive=True)]
      y = os.path.basename(files[0]).split("-")[0]
      y2 = os.path.basename(files[0]).split("-")[1]
      return "{}-{}".format(y, y2)
  
  if __name__ == "__main__":
  
      args = docopt(__doc__)
  
      model = args["<model>"]
      base_dir = args["--basedir"] if args["--basedir"] else "../complete_results"
      country = args["--country"] if args["--country"] else "italy"
      future = "no-future" if args["--no-future"] else "future"
  
      # Read the baseline results and merge them
      model_path = os.path.join(base_dir, args["<model>"], future, country)
      season_years = get_results_filename(model_path)
      model_file = os.path.join(model_path, "{}-prediction.csv".format(season_years))
  
      # Load the data
      data = pd.read_csv(model_file)
  
      # Describe the data
      print("")
      print("[*] Describe the given dataset {}".format(model_file))
      print(data.describe())
  
      # Generate residuals
      print("")
      print("[*] Describe the residuals")
      residuals = data["incidence"]-data["prediction"]
      print(residuals.describe())
  
      # Get some statistics
      print("")
      print("Pearson Correlation (value/p): ", stats.pearsonr(data["prediction"], data["incidence"]))
      print("")
  
subject: Add file to get some basic statistics from the prediction.