src/nupic/regions/knn_classifier_region.py
def setParameter(self, name, index, value):
    """
    Overrides :meth:`nupic.bindings.regions.PyRegion.PyRegion.setParameter`.
    """
    if name == "learningMode":
      self.learningMode = bool(int(value))
      self._epoch = 0
    elif name == "inferenceMode":
      self._epoch = 0
      if int(value) and not self.inferenceMode:
        self._finishLearning()
      self.inferenceMode = bool(int(value))
    elif name == "distanceNorm":
      self._knn.distanceNorm = value
    elif name == "distanceMethod":
      self._knn.distanceMethod = value
    elif name == "keepAllDistances":
      self.keepAllDistances = bool(value)
      if not self.keepAllDistances:
        # Discard all distances except the latest
        if self._protoScores is not None and self._protoScores.shape[0] > 1:
          self._protoScores = self._protoScores[-1,:]
        if self._protoScores is not None:
          self._protoScoreCount = 1
        else:
          self._protoScoreCount = 0
    elif name == "verbosity":
      self.verbosity = value
      self._knn.verbosity = value
    else:
      return PyRegion.setParameter(self, name, index, value)
def setParameter(self, name, index, value):
    """
    Overrides :meth:`nupic.bindings.regions.PyRegion.PyRegion.setParameter`.
    """
    if name == "learningMode":
      self.learningMode = bool(int(value))
      self._epoch = 0
    elif name == "inferenceMode":
      self._epoch = 0
      if int(value) and not self.inferenceMode:
        self._finishLearning()
      self.inferenceMode = bool(int(value))
    elif name == "distanceNorm":
      self._knn.distanceNorm = value
    elif name == "distanceMethod":
      self._knn.distanceMethod = value
    elif name == "keepAllDistances":
      self.keepAllDistances = bool(value)
      if not self.keepAllDistances:
        # Discard all distances except the latest
        if self._protoScores is not None and self._protoScores.shape[0] > 1:
          self._protoScores = self._protoScores[-1,:]
        if self._protoScores is not None:
          self._protoScoreCount = 1
        else:
          self._protoScoreCount = 0
    elif name == "verbosity":
      self.verbosity = value
      self._knn.verbosity = value
    else:
      return PyRegion.setParameter(self, name, index, value)
def setParameter ( self , name , index , value ) : if name == "learningMode" : self . learningMode = bool ( int ( value ) ) self . _epoch = 0 elif name == "inferenceMode" : self . _epoch = 0 if int ( value ) and not self . inferenceMode : self . _finishLearning ( ) self . inferenceMode = bool ( int ( value ) ) elif name == "distanceNorm" : self . _knn . distanceNorm = value elif name == "distanceMethod" : self . _knn . distanceMethod = value elif name == "keepAllDistances" : self . keepAllDistances = bool ( value ) if not self . keepAllDistances : # Discard all distances except the latest if self . _protoScores is not None and self . _protoScores . shape [ 0 ] > 1 : self . _protoScores = self . _protoScores [ - 1 , : ] if self . _protoScores is not None : self . _protoScoreCount = 1 else : self . _protoScoreCount = 0 elif name == "verbosity" : self . verbosity = value self . _knn . verbosity = value else : return PyRegion . setParameter ( self , name , index , value )
Overrides :meth:`nupic.bindings.regions.PyRegion.PyRegion.setParameter`.
Overrides : meth : nupic . bindings . regions . PyRegion . PyRegion . setParameter .