def __init__(self,
               inputDimensions=[32,32],
               columnDimensions=[64,64],
               potentialRadius=16,
               potentialPct=0.9,
               globalInhibition=True,
               localAreaDensity=-1.0,
               numActiveColumnsPerInhArea=10.0,
               stimulusThreshold=2,
               synPermInactiveDec=0.01,
               synPermActiveInc=0.03,
               synPredictedInc=0.5,
               synPermConnected=0.3,
               minPctOverlapDutyCycle=0.001,
               dutyCyclePeriod=1000,
               boostStrength=0.0,
               useBurstingRule = False,
               usePoolingRule = True,
               poolingLife = 1000,
               poolingThreshUnpredicted = 0.0,
               initConnectedPct = 0.2,
               seed=-1,
               spVerbosity=0,
               wrapAround=True
               ):
    """
    Please see spatial_pooler.py in NuPIC for descriptions of common
    constructor parameters.

    Class-specific parameters:
    -------------------------------------

    @param synPredictedInc:
       In this model, a metabotropically active synapse is implemented as an
       active synapse whose input originates from a correctly predicted cell
       in Temporal Memory. synPredictedInc is then the amount of permanence
       added to each metabotropically active synapse in each round

    @param useBurstingRule:
      A Boolean indicating whether bursting columns in the TM will have a
      strong effect on overlap calculation

    @param usePoolingRule:
      A Boolean indicating whether inputs representing correctly predicted
      cells in the Temporal Memory will contribute to column overlap calculation

    @param poolingLife:
      The maximum number of timesteps that a pooling column will pool for
      in the absence of any predicted input.

    @param poolingThreshUnpredicted:
       A threshold, ranging from 0 to 1, on the fraction of bottom-up input that
       is unpredicted. If this threshold is exceeded, the temporal pooler will
       stop pooling across all TP cells.

    @param initConnectedPct:
      A number between 0 or 1 governing the chance, for each permanence, that
      the initial permanence value will be a value that is considered connected.
    """
    self.initialize(inputDimensions,
                    columnDimensions,
                    potentialRadius,
                    potentialPct,
                    globalInhibition,
                    localAreaDensity,
                    numActiveColumnsPerInhArea,
                    stimulusThreshold,
                    synPermInactiveDec,
                    synPermActiveInc,
                    synPredictedInc,
                    synPermConnected,
                    minPctOverlapDutyCycle,
                    dutyCyclePeriod,
                    boostStrength,
                    useBurstingRule,
                    usePoolingRule,
                    poolingLife,
                    poolingThreshUnpredicted,
                    seed,
                    initConnectedPct,
                    spVerbosity,
                    wrapAround)
def __init__ ( self , inputDimensions = [ 32 , 32 ] , columnDimensions = [ 64 , 64 ] , potentialRadius = 16 , potentialPct = 0.9 , globalInhibition = True , localAreaDensity = - 1.0 , numActiveColumnsPerInhArea = 10.0 , stimulusThreshold = 2 , synPermInactiveDec = 0.01 , synPermActiveInc = 0.03 , synPredictedInc = 0.5 , synPermConnected = 0.3 , minPctOverlapDutyCycle = 0.001 , dutyCyclePeriod = 1000 , boostStrength = 0.0 , useBurstingRule = False , usePoolingRule = True , poolingLife = 1000 , poolingThreshUnpredicted = 0.0 , initConnectedPct = 0.2 , seed = - 1 , spVerbosity = 0 , wrapAround = True ) : self . initialize ( inputDimensions , columnDimensions , potentialRadius , potentialPct , globalInhibition , localAreaDensity , numActiveColumnsPerInhArea , stimulusThreshold , synPermInactiveDec , synPermActiveInc , synPredictedInc , synPermConnected , minPctOverlapDutyCycle , dutyCyclePeriod , boostStrength , useBurstingRule , usePoolingRule , poolingLife , poolingThreshUnpredicted , seed , initConnectedPct , spVerbosity , wrapAround )
Please see spatial_pooler.py in NuPIC for descriptions of common
    constructor parameters.

    Class-specific parameters:
    -------------------------------------

    @param synPredictedInc:
       In this model, a metabotropically active synapse is implemented as an
       active synapse whose input originates from a correctly predicted cell
       in Temporal Memory. synPredictedInc is then the amount of permanence
       added to each metabotropically active synapse in each round

    @param useBurstingRule:
      A Boolean indicating whether bursting columns in the TM will have a
      strong effect on overlap calculation

    @param usePoolingRule:
      A Boolean indicating whether inputs representing correctly predicted
      cells in the Temporal Memory will contribute to column overlap calculation

    @param poolingLife:
      The maximum number of timesteps that a pooling column will pool for
      in the absence of any predicted input.

    @param poolingThreshUnpredicted:
       A threshold, ranging from 0 to 1, on the fraction of bottom-up input that
       is unpredicted. If this threshold is exceeded, the temporal pooler will
       stop pooling across all TP cells.

    @param initConnectedPct:
      A number between 0 or 1 governing the chance, for each permanence, that
      the initial permanence value will be a value that is considered connected.