content: # -*- coding: UTF-8 -*-
  """
  Plot visualization of user habits, i.e. show which actions typically follow some given user action.
     
  Note: the figure for "Frontdoor=Closed" slightly deviates from Figure 1 in the paper and Figure 5.1 in the
  dissertation (see paper_experiments.py for bibliographical information). The number of observed actions was reported
  correctly in the paper/dissertation, however there was an issue with ordering which actions occur most commonly,
  which resulted in "Open cups cupboard" being erroneously included in the figure. Despite this issue, the main point
  of the figure still stands: the user has some observable habits after closing the frontdoor.
  """
  
  import sys
  sys.path.append("..") 
  
  import pandas
  
  from recsys.classifiers.temporal import TemporalEvidencesClassifier
  from recsys.classifiers.binning import initialize_bins
  from recsys.dataset import load_dataset
  from evaluation import plot
  import config
  
  #configuration
  data = load_dataset("../datasets/houseA.csv", "../datasets/houseA.config")
  
  #fit classifier to dataset
  cls = TemporalEvidencesClassifier(data.features, data.target_names, bins=initialize_bins(0, 300, 10))
  cls = cls.fit(data.data, data.target)
  
  #create visualizations of habits around each user action
  plot_conf = plot.plot_config(config.plot_directory, sub_dirs=[data.name, "habits"], img_type=config.img_type)
  for source in cls.sources.values():
      observations = pandas.DataFrame(source.temporal_counts)
      observations.columns = data.target_names
      observations.index = cls.bins
      plot.plot_observations(source.name(), observations, plot_conf)
      
  print "Results can be found in the \"%s\" directory" % config.plot_directory
  