Experiments Tracking

The experiment tracking is performed automaticaly for all experiments executed using deep_nilmtk. Neverthless, the generated artifcats are not automaticaly linked in the experiments. It is done only if the user expliciltely specifies it using the corresponding parameter.

 experiment = {
   'power': {'mains': ['active'],'appliance': ['active']},
   'sample_rate': 6,
   'appliances': [
         'fridge',
         'washing machine',
             'dish washer',
       ],
   'artificial_aggregate': False,
   'DROP_ALL_NANS': True,
   'methods': {
           'WAVENILM': NILMExperiment({
                "model_name": 'WAVENILM',
                'context_size': 481,
                'input_norm':'z-norm',
                'target_norm':'z-norm',
                'feature_type':'mains',
                'max_nb_epochs':max_nb_epochs,
                'log_artificat':True,
                }),
   },

   'train': {
     'datasets': {
      data: {
         'path': data_path,
         'buildings': {
               1: {
                     'start_time': '2015-01-04',
                     'end_time': '2015-03-30'
           }
         }
      }
     }
   },
     'test': {
     'datasets': {

       data: {
         'path': data_path,
         'buildings': {
               1: {
                     'start_time': '2015-04-16',
                     'end_time': '2015-05-15'
                 }
         }
       }
     },
         'metrics':['mae','nde','f1score', 'rmse']
     }

 }