src/nupic/swarming/exp_generator/experiment_generator.py
def _handleJAVAParameters(options):
  """ Handle legacy options (TEMPORARY) """

  # Find the correct InferenceType for the Model
  if 'inferenceType' not in options:
    prediction = options.get('prediction', {InferenceType.TemporalNextStep:
                                              {'optimize':True}})
    inferenceType = None
    for infType, value in prediction.iteritems():
      if value['optimize']:
        inferenceType = infType
        break

    if inferenceType == 'temporal':
      inferenceType = InferenceType.TemporalNextStep
    if inferenceType != InferenceType.TemporalNextStep:
      raise _ExpGeneratorException("Unsupported inference type %s"  % \
                                    (inferenceType))
    options['inferenceType'] = inferenceType

  # Find the best value for the predicted field
  if 'predictionField' in options:
    if 'inferenceArgs' not in options:
      options['inferenceArgs'] = {'predictedField': options['predictionField']}
    elif 'predictedField' not in options['inferenceArgs']:
      options['inferenceArgs']['predictedField'] = options['predictionField']
def _handleJAVAParameters(options):
  """ Handle legacy options (TEMPORARY) """

  # Find the correct InferenceType for the Model
  if 'inferenceType' not in options:
    prediction = options.get('prediction', {InferenceType.TemporalNextStep:
                                              {'optimize':True}})
    inferenceType = None
    for infType, value in prediction.iteritems():
      if value['optimize']:
        inferenceType = infType
        break

    if inferenceType == 'temporal':
      inferenceType = InferenceType.TemporalNextStep
    if inferenceType != InferenceType.TemporalNextStep:
      raise _ExpGeneratorException("Unsupported inference type %s"  % \
                                    (inferenceType))
    options['inferenceType'] = inferenceType

  # Find the best value for the predicted field
  if 'predictionField' in options:
    if 'inferenceArgs' not in options:
      options['inferenceArgs'] = {'predictedField': options['predictionField']}
    elif 'predictedField' not in options['inferenceArgs']:
      options['inferenceArgs']['predictedField'] = options['predictionField']
def _handleJAVAParameters ( options ) : # Find the correct InferenceType for the Model if 'inferenceType' not in options : prediction = options . get ( 'prediction' , { InferenceType . TemporalNextStep : { 'optimize' : True } } ) inferenceType = None for infType , value in prediction . iteritems ( ) : if value [ 'optimize' ] : inferenceType = infType break if inferenceType == 'temporal' : inferenceType = InferenceType . TemporalNextStep if inferenceType != InferenceType . TemporalNextStep : raise _ExpGeneratorException ( "Unsupported inference type %s" % ( inferenceType ) ) options [ 'inferenceType' ] = inferenceType # Find the best value for the predicted field if 'predictionField' in options : if 'inferenceArgs' not in options : options [ 'inferenceArgs' ] = { 'predictedField' : options [ 'predictionField' ] } elif 'predictedField' not in options [ 'inferenceArgs' ] : options [ 'inferenceArgs' ] [ 'predictedField' ] = options [ 'predictionField' ]
Handle legacy options (TEMPORARY)
Handle legacy options ( TEMPORARY )