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 HTMPredictionModelInvalidArgument(
"Invalid argument type \'%s\'. threshold "
"must be a number." % (type(value)))
if len(self._recordsCache
) > 0 and value < self._recordsCache[0].ROWID:
raise HTMPredictionModelInvalidArgument(
"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 HTMPredictionModelInvalidArgument(
"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 HTMPredictionModelInvalidArgument(
"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 setAutoDetectWaitRecords(self, waitRecords):
"""
Sets the autoDetectWaitRecords.
"""
if not isinstance(waitRecords, int):
raise HTMPredictionModelInvalidArgument("Invalid argument type \'%s\'. WaitRecord "
"must be a number." % (type(waitRecords)))
if len(self.saved_states) > 0 and waitRecords < self.saved_states[0].ROWID:
raise HTMPredictionModelInvalidArgument("Invalid value. autoDetectWaitRecord value "
"must be valid record within output stream. Current minimum ROWID in "
"output stream is %d." % (self.saved_states[0].ROWID))
self._autoDetectWaitRecords = waitRecords
# Update all the states in the classifier's cache
for state in self.saved_states:
self._updateState(state)
def setAutoDetectThreshold(self, threshold):
"""
Sets the autoDetectThreshold.
TODO: Ensure previously classified points outside of classifier are valid.
"""
if not (isinstance(threshold, float) or isinstance(threshold, int)):
raise HTMPredictionModelInvalidArgument("Invalid argument type \'%s\'. threshold "
"must be a number." % (type(threshold)))
self._autoDetectThreshold = threshold
# Update all the states in the classifier's cache
for state in self.saved_states:
self._updateState(state)