code: def gen_feats(self, p_set):
          
          if self._initialized!=True:
              error_message = "Dictionaries have not been initialized."
              log.exception(error_message)
              raise util_functions.InputError(p_set, error_message)
  
          textual_features = []
          for i in xrange(0,len(p_set._essay_sets)):
              textual_features.append(self._extractors[i].gen_feats(p_set._essay_sets[i]))
  
          textual_matrix = numpy.concatenate(textual_features, axis=1)
          predictor_matrix = numpy.array(p_set._numeric_features)
  
          print textual_matrix.shape
          print predictor_matrix.shape
  
          overall_matrix = numpy.concatenate((textual_matrix, predictor_matrix), axis=1)
  
          return overall_matrix.copy()
docs: Generates features based on an iput p_set
          p_set - PredictorSet