def __init__(self, prob=.5, size=20): self.n = size self.p = prob Distribution.__init__(self, self.calculate_mean(), self.calculate_stdev())
def __init__(self, prob=.5, size=20): # TODO: store the probability of the distribution in an instance variable p self.p = prob # TODO: store the size of the distribution in an instance variable n self.n = size # TODO: Now that you know p and n, you can calculate the mean and standard deviation # Use the calculate_mean() and calculate_stdev() methods to calculate the # distribution mean and standard deviation self.mean = self.calculate_mean() self.stdev = self.calculate_stdev() # Then use the init function from the Distribution class to initialize the # mean and the standard deviation of the distribution Distribution.__init__(self, self.mean, self.stdev)
def __init__(self, parmA,parmB): Distribution.__init__(self) self.parmA = parmA self.parmB = parmB
def __init__(self, parmM,parmG): Distribution.__init__(self) self.parmM = parmM self.parmG = parmG
def __init__(self, parmM, parmG): Distribution.__init__(self) self.parmM = parmM self.parmG = parmG
def __init__(self, mu=0, sigma=1): Distribution.__init__(self, mu, sigma)
def __init__(self,listOFparms): Distribution.__init__()
def __init__(self, parmA, parmB): Distribution.__init__(self) self.parmA = parmA self.parmB = parmB
def __init__(self, Map={}): Distribution.__init__(self) #map is a python dictionary{[time,count]..} self.map = Map
def __init__(self,Map = {}): Distribution.__init__(self) #map is a python dictionary{[time,count]..} self.map = Map