code: def getParameter(self, name, index=-1):
      
      if name == "patternCount":
        return self._knn._numPatterns
      elif name == "patternMatrix":
        return self._getPatternMatrix()
      elif name == "k":
        return self._knn.k
      elif name == "distanceNorm":
        return self._knn.distanceNorm
      elif name == "distanceMethod":
        return self._knn.distanceMethod
      elif name == "distThreshold":
        return self._knn.distThreshold
      elif name == "inputThresh":
        return self._knn.binarizationThreshold
      elif name == "doBinarization":
        return self._knn.doBinarization
      elif name == "useSparseMemory":
        return self._knn.useSparseMemory
      elif name == "sparseThreshold":
        return self._knn.sparseThreshold
      elif name == "winnerCount":
        return self._knn.numWinners
      elif name == "relativeThreshold":
        return self._knn.relativeThreshold
      elif name == "SVDSampleCount":
        v = self._knn.numSVDSamples
        return v if v is not None else 0
      elif name == "SVDDimCount":
        v = self._knn.numSVDDims
        return v if v is not None else 0
      elif name == "fractionOfMax":
        v = self._knn.fractionOfMax
        return v if v is not None else 0
      elif name == "useAuxiliary":
        return self._useAuxiliary
      elif name == "justUseAuxiliary":
        return self._justUseAuxiliary
      elif name == "doSphering":
        return self._doSphering
      elif name == "cellsPerCol":
        return self._knn.cellsPerCol
      elif name == "maxStoredPatterns":
        return self.maxStoredPatterns
      elif name == 'categoryRecencyList':
        return self._knn._categoryRecencyList
      else:
        # If any spec parameter name is the same as an attribute, this call
        # will get it automatically, e.g. self.learningMode
        return PyRegion.getParameter(self, name, index)
docs: Overrides :meth:`nupic.bindings.regions.PyRegion.PyRegion.getParameter`.