Exemple #1
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    # Iteration count: maximum number of iterations.  Each iteration corresponds
    # to one record from the (possibly aggregated) dataset.  The task is
    # terminated when either number of iterations reaches iterationCount or
    # all records in the (possibly aggregated) database have been processed,
    # whichever occurs first.
    #
    # iterationCount of -1 = iterate over the entire dataset
    #'iterationCount' : ITERATION_COUNT,

    # Metrics: A list of MetricSpecs that instantiate the metrics that are
    # computed for this experiment
    'metrics': [
        MetricSpec(field=u'consumption',
                   inferenceElement=InferenceElement.prediction,
                   metric='rmse'),
    ],

    # Logged Metrics: A sequence of regular expressions that specify which of
    # the metrics from the Inference Specifications section MUST be logged for
    # every prediction. The regex's correspond to the automatically generated
    # metric labels. This is similar to the way the optimization metric is
    # specified in permutations.py.
    'loggedMetrics': ['.*nupicScore.*'],
}

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descriptionInterface = ExperimentDescriptionAPI(modelConfig=config,
                                                control=control)
Exemple #2
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      # the metrics from the Inference Specifications section MUST be logged for
      # every prediction. The regex's correspond to the automatically generated
      # metric labels. This is similar to the way the optimization metric is
      # specified in permutations.py.
      'loggedMetrics': [],
      
      # Callbacks for experimentation/research (optional)
      'callbacks' : {
        # Callbacks to be called at the beginning of a task, before model iterations.
        # Signature: callback(<reference to OPFExperiment>); returns nothing
        'setup' : [claModelControlEnableSPLearningCb, claModelControlEnableTPLearningCb],
        
        # Callbacks to be called after every learning/inference iteration
        # Signature: callback(<reference to OPFExperiment>); returns nothing
        'postIter' : [],
        
        # Callbacks to be called when the experiment task is finished
        # Signature: callback(<reference to OPFExperiment>); returns nothing
        'finish' : []
      }
    } # End of taskControl
  }, # End of task
]



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descriptionInterface = ExperimentDescriptionAPI(modelConfig=config,
                                                taskList=tasks)