def setParameter(self, name, index, value): """Set the value of a parameter.""" if name == "SVDSampleCount": self._SVDSampleCount = value elif name == "logPath": self._logPath = value else: PyRegion.setParameter(self, name, index, value)
def setParameter(self, name, index, value): """ Set the value of the parameter. @param name -- the name of the parameter to update, as defined by the Node Spec. @param value -- the value to which the parameter is to be set. """ if name == "learningMode": self.learningMode = bool(int(value)) elif name == "inferenceMode": self.inferenceMode = bool(int(value)) else: return PyRegion.setParameter(self, name, index, value)
def setParameter(self, name, index, value): """ Set the value of the parameter. @param name -- the name of the parameter to update, as defined by the Node Spec. @param value -- the value to which the parameter is to be set. """ if name == "trainRecords": # Ensure that the trainRecords can only be set to minimum of the ROWID in # the saved states if not (isinstance(value, float) or isinstance(value, int)): raise CLAModelInvalidArgument( "Invalid argument type \'%s\'. threshold " "must be a number." % (type(value))) if len(self._recordsCache ) > 0 and value < self._recordsCache[0].ROWID: raise CLAModelInvalidArgument( "Invalid value. autoDetectWaitRecord " "value must be valid record within output stream. Current minimum " " ROWID in output stream is %d." % (self._recordsCache[0].ROWID)) self.trainRecords = value # Remove any labels before the first cached record (wont be used anymore) self._deleteRangeFromKNN(0, self._recordsCache[0].ROWID) # Reclassify all states self.classifyStates() elif name == "anomalyThreshold": if not (isinstance(value, float) or isinstance(value, int)): raise CLAModelInvalidArgument( "Invalid argument type \'%s\'. threshold " "must be a number." % (type(value))) self.anomalyThreshold = value self.classifyStates() elif name == "classificationMaxDist": if not (isinstance(value, float) or isinstance(value, int)): raise CLAModelInvalidArgument( "Invalid argument type \'%s\'. " "classificationMaxDist must be a number." % (type(value))) self._classificationMaxDist = value self.classifyStates() elif name == "activeColumnCount": self._activeColumnCount = value else: return PyRegion.setParameter(self, name, index, value)
def setParameter(self, name, index, value): """ Set the value of the parameter. @param name -- the name of the parameter to update, as defined by the Node Spec. @param value -- the value to which the parameter is to be set. """ if name == "trainRecords": # Ensure that the trainRecords can only be set to minimum of the ROWID in # the saved states if not (isinstance(value, float) or isinstance(value, int)): raise CLAModelInvalidArgument("Invalid argument type \'%s\'. threshold " "must be a number." % (type(value))) if len(self._recordsCache) > 0 and value < self._recordsCache[0].ROWID: raise CLAModelInvalidArgument("Invalid value. autoDetectWaitRecord " "value must be valid record within output stream. Current minimum " " ROWID in output stream is %d." % (self._recordsCache[0].ROWID)) self.trainRecords = value # Remove any labels before the first cached record (wont be used anymore) self._deleteRangeFromKNN(0, self._recordsCache[0].ROWID) # Reclassify all states self.classifyStates() elif name == "anomalyThreshold": if not (isinstance(value, float) or isinstance(value, int)): raise CLAModelInvalidArgument("Invalid argument type \'%s\'. threshold " "must be a number." % (type(value))) self.anomalyThreshold = value self.classifyStates() elif name == "classificationMaxDist": if not (isinstance(value, float) or isinstance(value, int)): raise CLAModelInvalidArgument("Invalid argument type \'%s\'. " "classificationMaxDist must be a number." % (type(value))) self._classificationMaxDist = value self.classifyStates() elif name == "activeColumnCount": self._activeColumnCount = value else: return PyRegion.setParameter(self, name, index, value)
def setParameter(self, name, index, value): """ Set the value of the parameter. @param name -- the name of the parameter to update, as defined by the Node Spec. @param value -- the value to which the parameter is to be set. """ if name == "learningMode": if int(value) and not self.learningMode: self._restartLearning() 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 == "clVerbosity": self.verbosity = value self._knn.verbosity = value elif name == "doSelfValidation": self.doSelfValidation = value else: return PyRegion.setParameter(self, name, index, value)
def setParameter(self, name, index, value): """ Set the value of the parameter. @param name -- the name of the parameter to update, as defined by the Node Spec. @param value -- the value to which the parameter is to be set. """ if name == "learningMode": if int(value) and not self.learningMode: self._restartLearning() 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 == "clVerbosity": self.verbosity = value self._knn.verbosity = value elif name == "doSelfValidation": self.doSelfValidation = value else: return PyRegion.setParameter(self, name, index, value)