def __init__(self, dependency='x', isPopulation=False):
super(Variance, self).__init__(dependency)
_checkParameterList(dependency)
self._currentSum = 0.0
self._currentSumSquare = 0.0
self._currentCount = 0
self._isPop = isPopulation
self._returnSize = 1
def __init__(self, dependency='x', isPopulation=False):
super(Variance, self).__init__(dependency)
_checkParameterList(dependency)
self._currentSum = 0.0
self._currentSumSquare = 0.0
self._currentCount = 0
self._isPop = isPopulation
self._returnSize = 1
def __init__(self, dependency='x'):
super(Average, self).__init__(dependency)
_checkParameterList(dependency)
self._currentSum = 0.0
self._currentCount = 0
self._returnSize = 1
def __init__(self, dependency='x'):
super(Minimum, self).__init__(dependency)
_checkParameterList(dependency)
self._currentMin = None
self._returnSize = 1
def __init__(self, dependency='x'):
super(Latest, self).__init__(dependency)
_checkParameterList(dependency)
self._returnSize = 1
self._latest = None
def __init__(self, dependency='x'):
super(Average, self).__init__(dependency)
_checkParameterList(dependency)
self._currentSum = 0.0
self._currentCount = 0
self._returnSize = 1
def __init__(self, dependency='x'):
super(Minimum, self).__init__(dependency)
_checkParameterList(dependency)
self._currentMin = None
self._returnSize = 1
