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
