def __init__(self,
               numInputBits=41,
               sensorInputSize=2048,
               externalInputSize=2048,
               numCorticalColumns=1,
               numFeatures=400,
               dimension=3,
               seed=42):
    """
    At creation, the SimpleObjectMachine creates a pool of locations and
    features SDR's.

    Parameters:
    ----------------------------
    @param   numInputBits (int)
             Number of ON bits in the input. Note: it should be uneven as the
             encoder only accepts uneven number of bits.

    @param   sensorInputSize (int)
             Total number of bits in the sensory input

    @param   externalInputSize (int)
             Total number of bits the external (location) input

    @param   numCorticalColumns (int)
             Number of cortical columns used in the experiment

    @param   dimension (int)
             Dimension of the locations. Will typically be 3.

    @param   numFeatures (int)
             Number of feature SDRs to generate per cortical column. There is
             typically no need to not use the default value, unless the user
             knows he will use more than 400 patterns.

    @param   seed (int)
             Seed to be used in the machine

    """
    super(ContinuousLocationObjectMachine, self).__init__(numInputBits,
                                                          sensorInputSize,
                                                          externalInputSize,
                                                          numCorticalColumns,
                                                          seed)

    # location and features pool
    self.numFeatures = numFeatures
    self._generateFeatures()

    self.dimension = dimension
    self.locationEncoder = CoordinateEncoder(
      w=numInputBits,
      n=externalInputSize,
      name="locationEncoder"
    )
def __init__ ( self , numInputBits = 41 , sensorInputSize = 2048 , externalInputSize = 2048 , numCorticalColumns = 1 , numFeatures = 400 , dimension = 3 , seed = 42 ) : super ( ContinuousLocationObjectMachine , self ) . __init__ ( numInputBits , sensorInputSize , externalInputSize , numCorticalColumns , seed ) self . numFeatures = numFeatures self . _generateFeatures ( ) self . dimension = dimension self . locationEncoder = CoordinateEncoder ( w = numInputBits , n = externalInputSize , name = "locationEncoder" )
At creation, the SimpleObjectMachine creates a pool of locations and
    features SDR's.

    Parameters:
    ----------------------------
    @param   numInputBits (int)
             Number of ON bits in the input. Note: it should be uneven as the
             encoder only accepts uneven number of bits.

    @param   sensorInputSize (int)
             Total number of bits in the sensory input

    @param   externalInputSize (int)
             Total number of bits the external (location) input

    @param   numCorticalColumns (int)
             Number of cortical columns used in the experiment

    @param   dimension (int)
             Dimension of the locations. Will typically be 3.

    @param   numFeatures (int)
             Number of feature SDRs to generate per cortical column. There is
             typically no need to not use the default value, unless the user
             knows he will use more than 400 patterns.

    @param   seed (int)
             Seed to be used in the machine